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Writer's pictureRyan McCafferty

What The Metrics Had To Say About Pocono



The world of sports data is constantly changing, with more information than ever before available to teams, athletes, and even the common fan that can be used to predict performance trends. NASCAR is no different, and the author of this post has built a number of analytical metrics with the goal in mind of helping give race fans a more advanced view of the action on the track – because as any driver can attest to, auto racing isn’t always a fair sport.


The following numbers – explained in full detail here – are designed to measure driver performance in various aspects of each race, with many of them coming from NASCAR’s Loop Data. They are ranked by True Driver Rating (TDR), a variation on NASCAR’s Driver Rating which incorporates factors such as speed, track position, passing, luck, and equipment strength in order to best estimate how well each driver performed during an event.


The metrics from Sunday’s Great American Getaway 400 at Pocono Raceway are as shown below:


 

Denny Hamlin, who finished second behind Ryan Blaney in the race, recorded the top TDR score of the day at 256.11. Hamlin led the field in Average Running Position (5.0) and had an impressive Pass Differential (+29), two of the primary components that make up the TDR formula. Hamlin additionally scored .4748 Expected Wins Earned (XWE), meaning if Sunday's race was simulated an infinite number of times, he could have been expected to win roughly 47.48% of the time.


Chase Elliott was the only driver aside from Hamlin to reach the 200s, once again with Pass Differential being a primary factor. Elliott's +55 number in that column was the best of any driver in the field, as was his True Pass Differential (TPD) of 27.932 and his True Passer Rating (TPR) of 118.79. The former of those numbers adjusts for the amount of total passes in the race, while the latter weighs passes further up in the field as more impressive than others.


It is worth noting that passing numbers can be deceiving, though, which is the case for Blaney, who scored only the eighth-best TDR at 149.45 despite his win. At big tracks such as Pocono in which it's possible to pit under green without losing a lap, pit strategy can massively skew Pass Differential. Blaney lost about 30 positions when he made a stop before the end of Stage 2, just to then regain all of those spots under caution.


Blaney ultimately won the race in large part due to that strategy play rather than with his performance on the track, so it's understandable he did not have the highest score. However, he certainly had better than the eighth-best race and may have even had the fastest car aside from Hamlin and Elliott. Unfortunately every metric has its flaws, and since there is no way to eliminate passes during green-flag pit stops from the differential, Blaney takes a hit this week.


Brad Keselowski and Tyler Reddick ended up third and fourth in the metrics, respectively, while one more driver is worthy of a shoutout. That would be Erik Jones, who finished 14th with what would seem to be solid, yet unspectacular underlying numbers (11.8 ARP, +23 PD). Yet what boosts his score the most is that he massively outperformed his Legacy Motor Club equipment, outrunning teammate John Hunter Nemechek by an average of more than a dozen spots throughout the race.


Finally, Alex Bowman sticks out as an outlier further down the list, ranking only 15th in TDR despite his third-place finish. Bowman was one of the prime beneficiaries of the strategy game, emerging near the front at the end thanks to some timely quick work by his crew. The metrics can be kind to drivers who finish better than they run when they overcome adversity to climb into contention, but Bowman's overall performance wasn't enough to move the needle.


All things considered though, it ended up being a rather fair finishing order. The fairness rating of .7895 is towards the upper echelon of scores this season, and that's in spite of this being a race where pit strategy was more responsible for many drivers' results than their speed on the track. All races will have some degree of randomness to them, and there's nothing wrong with that -- after all, that's the whole reason why analytics exist.

 

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